Triple
T10970295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WTA Grand Slam |
E259214
|
entity |
| Predicate | impactOnRankings |
P46779
|
FINISHED |
| Object | major determinant of WTA rankings |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: major determinant of WTA rankings | Statement: [WTA Grand Slam, impactOnRankings, major determinant of WTA rankings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactOnRankings Context triple: [WTA Grand Slam, impactOnRankings, major determinant of WTA rankings]
-
A.
rankingImpact
Indicates how an entity’s position or level in a ranking is affected or influenced by another factor or action.
-
B.
impactOnStandings
chosen
Indicates how an event or outcome affects the relative rankings or standings within a competition or system.
-
C.
peakRanking
Indicates the highest position or rank an entity has ever achieved within a specified ranking system or context.
-
D.
rankingScope
Indicates the context or domain within which a ranking is defined, interpreted, or applied.
-
E.
impactOnPerformance
Indicates that one entity has an effect, influence, or consequence on the performance level or effectiveness of another entity.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d6aa895f4c8190887a15460ef622f4 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d77198e5408190904b2bb603d1bc16 |
completed | April 9, 2026, 9:30 a.m. |
| PD | Predicate disambiguation | batch_69d72e8c27cc81908050590b7a04cafd |
completed | April 9, 2026, 4:43 a.m. |
Created at: April 8, 2026, 9:24 p.m.